### MicroMasters Program in Statistics and Data Science Basics

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What is the MITx MicroMasters Program® Credential in Statistics and Data Science?
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From probability and statistics to data analysis and machine learning, master the skills needed to solve complex challenges with data. This program is composed of three core courses, plus one of two electives, developed by faculty at MIT and administered by Institute for Data, Systems, and Society.

The MITx MicroMasters program credential consists of four intensive online courses, consisting of three core courses and one elective, which provide learners with both foundational knowledge essential to understanding methods and tools used in data science and with hands-on practice. Students will practice implementing and experimenting with data analysis techniques and machine learning algorithms. After students complete these four courses there is one virtually-proctored Capstone Exam to complete the program and earn the credential.

It is important to note that the MicroMasters program is NOT a degree-granting program, nor is it a guarantee of admissions to MIT or to any of the IDSS graduate programs. It is a separate stand-alone professional certificate offered by MITx and delivered by edX. Read more or enroll on edX here.

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What are the four online courses required for the MITx MicroMasters Program Credential in Statistics and Data Science?
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There are four online courses, consisting of three core courses and one elective, and a Capstone Exam required to complete the MITx MicroMasters program credential in Statistics and Data Science.

Core courses:

- 6.431x Probability - The Science of Uncertainty and Data
- 6.86x Machine Learning with Python: from Linear Models to Deep Learning
- 18.6501x Fundamentals of Statistics

Electives in Data Analysis

- 6.419x Data Analysis: Statistical Modeling and Computation in Applications
- 14.310x/14.310Fx- Data Analysis in Social Science.
*This course consists of 2 parts: the content course 14.310x Data Analysis for Social Scientists and its SDS Exam: 14.310Fx Data Analysis in Social Sciences–Assessing your Knowledge. This course does NOT require probability as prerequisite. For more information on the setup of this course, please view the enrollment**logistics video**.*

To be eligible for the MicroMasters program credential, you must earn a Verified Certificate in each course and pass the comprehensive exam. Read more about verification here.

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What is the difference between two Data Analysis Electives?
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The two electives in Data Analysis are split into two categories:

- General Track
- Social Sciences Track

**General Track**

Through the General track course is Statistical Modeling and Computation in Application, learn probability, statistics, machine learning, and common models to analyze data, from image recognition to networks and time series.

**Social Sciences Track**

Through Social Sciences track with Data Analysis learn probability, statistics, and machine learning, and apply your knowledge to address complex societal challenges.

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Is there a suggested order in which I need to take the courses?
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We recommend that learners take one course per term.

Learners can choose to start the program with 6.431x (Probability), 14.310x/Fx (Data Analysis), or 6.86x (Machine Learning).

The constraints on ordering are:

- 6.431x (Probability) or an equivalent course is necessary before 18.6501x (Statistics).
- 14.310x/Fx (Data Analysis elective) is better before 18.6501x.
- 6.419x (Data Analysis: Statistical Modeling and Computation in Applications) is better after the other 3 courses.

Below are some examples of course sequences that work with the program schedule:

6.431x (Probability) → 6.86x (Machine Learning) → 18.6501x (Statistics) → 6.419x (nData Analysis: Statistical Modeling and Computation in Applications)

6.431x (Probability)→14.310x/Fx (Data Analysis: Statistical Modeling and Computation in Applications)→18.6501x (Statistics) 6.86x (Machine learning).

14.310x/Fx -6.41 Probability - Machine Learning - *Statistics (depends on the availability of 14.310 run).

6.86x (Machine Learning) → 6.431x (Probability) → 14.310x/Fx (Data Analysis elective) → 18.6501x (Statistics).

6.86x (Machine Learning) → 6.431x (Probability) → term break → 18.6501x (Statistics) → 6.419x (Data Analysis: Statistical Modeling and Computation in Applications).

Ambitious learners could choose to take courses concurrently (subject to the constraints above), and finish in 3 or even 2 terms (+ the capstone exam). The terms coincide roughly with MIT semesters.

If you do not have a strong probability background and would like to start pursuing the MicroMasters program in SDS during the term when 6.431x Probability course is not running, please enroll in with course 2 (14.310x Data Analysis in Social Sciences) of 4 in the program.

To succeed in the program, learners are strongly recommended to complete coursework from Introduction to Computer Science and Programming in Python (6.0001) or if possible: Introduction to Computational Thinking and Data Science (6.0002).

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Are these classes occurring again?
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Yes, the courses will be running in the future, in order to provide learners flexibility and opportunities to complete and schedule their coursework.

The next run of each course are also listed in the MITx MicroMasters program dashboard.

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What is the projected timeline?
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Below are some examples of course sequences that work with the program schedule:

6.431x (Probability) → 6.86x (Machine Learning) → 18.6501x (Statistics) → 6.419x (Data Analysis: Statistical Modeling and Computation in Applications).

6.431x (Probability)→14.310x/Fx (Data analysis elective)→→18.6501x (Statistics) 6.86x (Machine learning).

14.310x/Fx -6.41 Probability - Machine Learning - Statistics (add asterisk - depends on the availability of 14.310 run)

6.86x (Machine Learning) → 6.431x (Probability) → 14.310x/Fx (Data Analysis elective) → 18.6501x (Statistics).

6.86x - 6.431x-18.6501x-6.419x (term break between 6.431 and 18.6501) Just add into the line

Ambitious learners could choose to take courses concurrently (subject to the constraints above), and finish in 3 or even 2 terms (+ the capstone exam). The terms coincide roughly with MIT semesters.

If you do not have a strong probability background and would like to start pursuing the MicroMasters program in SDS during the term when 6.431x Probability course is not running, please enroll in with course 2 (14.310x Data Analysis in Social Sciences) of 4 in the program.

To succeed in the program, learners are strongly recommended to complete coursework from Introduction to Computer Science and Programming in Python (6.0001) or if possible: Introduction to Computational Thinking and Data Science (6.0002).

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What is the current and upcoming schedule for courses?
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Here are some current and future run dates for the courses that may help you decide how you would like to structure your course schedule.

*Notes - All dates are tentative and subject to change by 1-2 weeks.*

*All course listings are subject to change.*

*Dates for the 2022 SDS calendar are forthcoming.*

**2021 MM SDS Schedule**

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Is one course a pre-requisite for another course? In other words, do learners need to take the four courses in order or can they take some courses concurrently?
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We recommend that learners take one course per term.

Learners can choose to start the program with 6.431x (Probability), 14.310x/Fx (Data Analysis), or 6.86x (Machine Learning).

The constraints on ordering are:

- 6.431x (Probability) or an equivalent course is necessary before 18.6501x (Statistics).
- 14.310x/Fx (Data Analysis elective) is better before 18.6501x.
- 6.419x (Data Analysis: Statistical Modeling and Computation in Applications) is better after the other 3 courses.

Below are some examples of course sequences that work with the program schedule:

6.431x (Probability)→14.310x/Fx (Data analysis elective)→6.86x (Machine learning)→18.6501x (Statistics).

6.86x (Machine Learning) → 6.431x (Probability) → 14.310x/Fx (Data Analysis elective) → 18.6501x (Statistics).

6.431x (Probability) → 6.86x (Machine Learning) → 18.6501x (Statistics) → 6.419x (Data Analysis: Statistical Modeling and Computation in Applications).

Ambitious learners could choose to take courses concurrently (subject to the constraints above), and finish in 3 or even 2 terms (+ the capstone exam). The terms coincide roughly with MIT semesters.

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What are the prerequisites for the program?
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There are no mandated prerequisites or for the full program. Prerequisites for individual courses are listed on the respective course pages.

However, learners will excel only if they are comfortable with multi-variable calculus, math reasoning, and basic vectors and matrices before they start the program.

The following online courses on edX or MIT Open CourseWare (OCW) are recommended:

● Single variable calculus: 18.01.1x, 18.01.2x, 18.01.3x (Archived on edX)

● Multivariable calculus: 18.02 (OCW)

● Basics of Linear algebra:

○ Quick introduction: Units 1-2 of 18.033x (Archived on edX)

○ In-depth: 18.06 (OCW)

● Python programming: 6.00.1x (self-paced on edX)

*We strongly recommend the completion of “Multivariable Calculus” on MIT OpenCourseWare before starting any of the MITx MicroMasters program credential in Statistics and Data Science courses.

**Please also note, Python will not be taught in the SDS course Machine Learning with Python. We expect proficiency in Python. Learners without Python proficiency must take Introduction to Computer Science and Programming in Python (6.0001) and/or Introduction to Computational Thinking and Data Science (6.0002). One or both must be completed before pursuing course 6.86x Machine Learning with Python, where it will be used to implement machine learning algorithms. R will be reviewed.

Learners with no Python or cCalculus background should anticipate the cost of the program to remain the same, but the length of the program to be longer. Please anticipate all of the following courses:

**Audit for free:**

- Single variable calculus: 18.01.1x, 18.01.2x, 18.01.3x (Archived on edX)
- Multivariable calculus: 18.02 (OCW)
- Basics of Linear algebra:
- Quick introduction: Units 1-2 of 18.033x (Archived on edX)
- In-depth: 18.06 (OCW)

- Python programming: 6.00.1x (self-paced on edX)**
- Introduction to Computational Thinking and Data Science
- Data Analysis for Social Scientists, content course

**Pay as a Verified Learner for Three core courses:**

- Probability
- Fundamentals of Statistics
- Machine Learning with Python

**And one of the two electives on Data Analysis:**

- Data Analysis in Social Science: Assessing Your Knowledge
- Data Analysis: Statistical Modeling and Computation in Applications.

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How do I register for courses, and do I need to have an undergraduate degree?
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There is no formal admission to the MicroMasters programs. Please register for each individual course as your schedule permits on edX. Course enrollments are open to anyone, anywhere with an internet connection. An undergraduate degree is not required to enroll.

Given that these are graduate-level quantitative courses, we strongly suggest you have a grasp of single and multi-variable calculus and linear algebra, as well as being comfortable with mathematical reasoning and Python programming. Please see pre-requisite question above for information about background knowledge necessary for success.

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Do I need to be a Verified Learner to earn the MITx MicroMasters Program credential in Statistics and Data Science?
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Yes. You must successfully pass and receive a Verified Certificate in each of the four courses (3 core and 1 elective) and the Capstone Exam. Learn more about verified certificates here.

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How are the courses delivered?
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All courses are pre-recorded. Lessons are released according to a calendar specific to each course. The calendar will be posted at the beginning of each course. Students can work through the course content on their own schedule after it has been released. Please note some assignments have strict deadlines and work will not be accepted after that deadline.

If you are uncertain of your ability to commit to a course schedule, enroll in the course on the audit track and the schedule will become available on the start date of the class. You can determine after the first class if you would like to upgrade to Verified Learner status once you are certain about your schedule. The deadline to become a Verified Learner for a course is four weeks after the start date of the course.

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If you have never taken a course on edX you can try Demo_x:
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https://www.edx.org/course/demox-edx-demox-1-0

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How much does the MITx MicroMasters program credential in SDS cost, and is there financial aid available?
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The cost to take each course is US $300. The Capstone Exam cost is US $300. If you choose to enroll in and pay for each courses separately, your program cost will be $1500. If you choose to enroll in the program and pay for courses upfront, the program cost is $1350, for a savings of $150. Please see the program page on edX at the following link for more information.

edX offers financial aid to learners who qualify. You can learn more and find out if you qualify here.

If you choose to take courses on edX before beginning your program to enhance your background knowledge, such as calculus classes or Introduction to Python Programming, you do not need to pay for Verified Learner status for those courses. You only need to pay for the four required courses and the Capstone Exam.

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How long does it take to complete the MITx MicroMasters Program Credential in Statistics and Data Science?
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On average, we expect our learners to take about 12-18 months to complete the credential.

Learners with no Python or Calculus background should plan for 18-24 months. Please see the section on pre-requisites for more details.

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When is the next MITx MicroMasters program credential in Statistics and Data Science offered?
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The next run of each course are also listed in the MITx MicroMasters program dashboard and at the upcoming dates section.

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How much time should I expect to spend on each MITx MicroMasters program credential in Statistics and Data Science course?
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Each course in the MITx MicroMasters program credential in Statistics and Data Science runs for between 13 and 16 weeks. Learners with the appropriate background can expect to spend roughly 10-14 hours per week on each course.

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Is there a time limit to finish the MicroMasters program in Statistics and Data Science?
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There is no specific timeframe to complete the MicroMasters program, but if the learner is planning to use the credential to apply to a blended learning on-campus program, each program may have specific requirements.

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Is there any way to reduce the time needed to take and pass the MITx MicroMasters Program Credential in Statistics and Data Science courses and exam?
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To earn the MicroMasters Program Credential, you need to successfully earn a verified certificate in all MITx MicroMasters Program Credential in Statistics and Data Science online courses when they are scheduled and then pass the virtually-proctored exam. The courses are on an instructor-paced schedule rather than self-paced, so there is no way to reduce the time within in each individual course.

However, learners may take 14.310x (Data Analysis in Social Science) concurrently with 18.6501x (Fundamentals of Statistics) or 6.86x (Machine Learning with Python). This will allow you to complete the credentialing process earlier. Please refer to FAQ section on pre-requisites and the FAQ section on suggested course order for more information.

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May I use two or more different accounts for the MITx MicroMasters program credential in Statistics and Data Science courses?
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No. Each edX learner should have a **single** edX ID (username and email account) that must be used in the four MITx MicroMasters program credential in Statistics and Data Science courses and also in the final comprehensive exam. In fact, using two different edX accounts within the same course are grounds for expulsion from the course.

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I have taken similar courses as part of another program, can I get credit for these?
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Unfortunately we cannot give credit towards this credential for work completed outside these courses. You will need to take and pass all four courses and the Capstone Exam to receive this credential.

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Can I enroll in the Capstone Exam course before I have completed the four required courses?
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The option to enroll in the Capstone Exam course will only become available once final passing grades for all four required courses are on your dashboard. Then you will have the option to enroll in the Capstone Exam course.

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May I repeat a course for a better score?
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Yes, you may repeat a course as many times as you wish. Each offering of a course is assessed independently.

If you achieve passing scores on the audit track it will not count towards your credential. In order for a course to count toward the MicroMasters Program Credential, it must be taken as an I.D. Verified Learner. If you paid for the verified certificate track in your previous session and you did not pass or wish to try again for a better score, you will need to pay a new verified enrollment fee. Verified Learner status fee only applies to the session in which the fee was paid.

Verification fees are not transferable across courses.

Verification fees are not transferable across courses.

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What are the key concepts covered in each course?
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6.431x (Probability - The Science of Uncertainty and Data) is an introduction to probabilistic models, including random processes and the basic elements of statistical inference, and covers the foundations of data science.

6.86x (Machine Learning with Python) is an in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, with hands-on Python projects.

18.6501x (Fundamentals of Statistics) helps learners to develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing, and prediction.

6.419x Data Analysis: Statistical Modeling and Computation in Applications is hands on data analysis course that introduces the interplay between statistics and computation for the analysis of real data.

14.310x/Fx ( Data Analysis For Social Scientists/Data Analysis in Social Science: Assessing your Knowledge)covers the methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest. For more information on the special set up of this course please view the video.

The course pages can be found here: https://www.edx.org/micromasters/mitx-statistics-and-data-science#courses

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What if I have a disability-related request regarding accessing a MicroMasters program course or exam?
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If you have a disability-related request regarding accessing a MicroMasters program course or exam, please contact micromasters-support@mit.edu as early as possible.

### COURSES

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How are the courses scheduled? How often are assignments due?
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Each course varies. Assignments are often due weekly, and the release dates of the materials are correlated with these deadlines. Once you audit a course, you will have access to the syllabus and then decide if the assignment schedule will work for you.

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Which classes require R and which classes require Python?
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Python will be used in 6.86x (Machine Learning) and 6.419 (new Data Analysis elective), and R is covered in 14.310x (Data Analysis in Social Science). Please note, it is assumed learners are comfortable with Python before starting this MicroMasters program. R will be reviewed.

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Is there any operating system or software requirements for the courses?
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You will need to download R and Python. In addition, learners will need to download extra packages such as pytorch for the Machine Learning with Python course, and a software for virtual proctoring for the Capstone Exam.

There is no specific operating system preferred. If you search for the items that need to be downloaded you will find the operating systems to download them for.

For example Python is compatible with almost every OS including Windows, Linux/UNIX, Mac OS X, etc:

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Will I have access to the material after the course ends?
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Verified Learners will have access to the course material in archived mode once courses are finished. This may mean that videos are available but assessments, such as lecture and recitation exercises, homework, and exams, are not. As an audit learner, you will have access to the learning materials only while the course is open, but not an archived version once the course is closed. In order to maintain access to the learning materials, you are welcome to enroll as an auditor in any future run of a course.

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Do I have to take 14.310Fx Data Analysis in Social Science: Assessing Your Knowledge if I have taken and passed 14.310x Data Analysis for Social Scientists and the proctored exam as part of the DEDP MicroMasters program?
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If you have taken the 14.310x course and passed the proctored exams as a Verified Learner, you will not need to retake the course. However, you will need to pay for and take our assessment exam, Data Analysis in Social Science: Assessing Your Knowledge, as part of the MicroMasters program in Statistics and Data Science in order to receive a certificate for the course.

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Are the DEDP and SDS interchangeable credentials?
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To clarify, the MicroMasters programs in Data, Economics, and Development Policy (DEDP) and in Statistics and Data Science (SDS) are two independent programs. The cost of each class in DEDP (including the proctored exam) has recently changed -- see DEDP's site for more in depth information on these price changes. Do note that the certificates for SDS and DEDP are not interchangeable. If you are going to the SDS path, please enroll in the content course 14.310x - Data Analysis for Social Scientists (Note: There is no additional fee to enroll in the content course) and enroll in and pay for the assessment course; complete the content course 14.310x with a passing grade, then come back to the assessment course and take the exam to earn your verified certificate that will count toward the MicroMasters program credential in SDS.

This short video of Logistics of 14.310x/Fx Data Analysis for Social Scientists will help you understand the course better.

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What is the difference between 14.310x Data Analysis for Social Scientists and 14.310Fx (Data Analysis in Social Science)?
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14.310x (Data Analysis in Social Science) covers the methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest. 14.310Fx is an assessment that tests your knowledge on the course content from 14.310x (Data Analysis in Social Science).

This short video of Logistics of 14.310x/Fx Data Analysis for Social Scientists will help you understand the course better.

### CREDENTIALS AND VERIFIED CERTIFICATES

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Will I earn a separate certificate for each course or just one for the entire MicroMasters Program Credential?
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You will receive an individual Verified Certificate for each MITx MicroMasters course in the Statistics and Data Science program that you pass as a Verified Learner. Read more about course certificates here. View a sample course certificate here.

Learners who pass the Capstone Exam after earning all four required course certificates will receive the Statistics and Data Science MicroMasters credential.

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Does completion of the MicroMasters Program Credential guarantee admission to IDSS Graduate programs at MIT?
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No. While your performance in the MicroMasters program coursework and proctored exams will play a very important role in determining admissions, it won't be the only criterion we take into account.

Learners who successfully complete this MITx MicroMasters program credential have the opportunity to apply to the MIT Doctoral Program in Social and Engineering Systems (SES) offered through the MIT Institute for Data, Systems, and Society (IDSS) during the SES admissions cycle (due date: December 15). Credentialed learners will be able to use their credential to demonstrate their preparation in statistics and data science fundamentals to the SES Admissions Committee.

Learners admitted to SES can expect that their MITx MicroMasters program coursework will help prepare them for the SES core classes, and in many cases may also be applied toward the SES Information, Systems, and Decision Science requirements. More information on the MIT SES Doctoral Program can be found here (https://idss.mit.edu/academics/ses_doc/).

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How do I earn a Verified Certificate? When is the deadline to pay and verify for the course?
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To earn a verified certificate for each of the 4 online courses, you need to pay the fee and upgrade to Verified Learner Status before the payment/verify deadline, and then successfully complete the course with 60% or above.

The payment deadline for each specific course is listed on the course page on the right side under "Important Course Dates", and are roughly 1-2 months from the course start, with the exception of **14.310Fx** ** Data Analysis in Social Science-Assessing Your Knowledge**. The verified certificate costs US $300 per course in the MITx MicroMasters program credential in Statistics and Data Science.

For **14.310Fx** *Data Analysis in Social Science-Assessing Your Knowledge***,** because of the special setup, the payment deadline is generally when the exam course opens, and near the end of the 1**4.310x** ** Data Analysis for for Social Scientists** content course.

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How do I earn a Verified Certificate for the Capstone Exam? When is the deadline to pay and verify for the course?
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To earn a verified certificate for the virtually proctored Capstone exam, you need to first pass 4 online courses (3 core and 1 elective ) and verify before the deadline of the Capstone exam, which is generally when the capstone course starts. The virtually proctored exam is also US $300 and requires you to verify your identity using a webcam and a government-issued ID, so employers and schools know that you, and only you, completed the coursework.

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Which institution issues the verified certificate?
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Certificates are issued by edX under the name of MITx and are delivered online through edx.org.

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Is it sufficient to keep a "pass" grade in the course, or will the bar for achieving the MicroMasters program be set higher?
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Yes, you will receive your credential if you achieve a passing grade in each course and the Capstone Exam.

The passing grade for each course is independent of the MicroMasters program credential. The specific grade is set by the instructor. When applying to an MIT graduate program, we will use the actual scores in the admissions process – but that is independent of earning the MicroMasters program credential.

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How to view and share your Statistics and Data Science Program Record?
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Please review this detailed instruction from edX.

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How do I share my course certificate or MicroMasters program credential with employers and schools? How can I prove completion of the MicroMasters program?
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You can add the individual course certificate, or MicroMasters program credential in the education, certifications or accomplishments section of your resume or CV. If you wish to add the MicroMasters program credential abbreviation to your title, use “ MITx MicroMasters program credential in Statistics and Data Science.”

Your course certificate or MicroMasters program credential will have an identifying code that you can also share via hyperlink following these directions.

To add your course certificate or MicroMasters program credential to your LinkedIn profile, you may use the Education or Accomplishments sections of LinkedIn. Choose MITx as your certification authority under education or MIT IDSS under accomplishments.

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I've already taken Introduction to Probability when it was listed as 6.041x. Can I get credit for this course?
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If you took 6.041x as a Verified Learner and passed before September 2018, you can receive credit for 6.431x Probability - The Science of Uncertainty and Data. You will still need to verify and pass the other MicroMasters program courses and the cumulative final exam in order to complete the MicroMasters program credential. When enrolling for the final exam, please inform the staff of when you took 6.041x.

### ACADEMIC PROGRAMS AT MIT IDSS AND OTHER UNIVERSITIES

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What are the paths to earning a PhD Degree from MIT IDSS?
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The **Doctoral Program in Social and Engineering Systems (SES)** is a unique research program independent of the Micromasters Program in Statistics and Data Science.

Learners who successfully complete the MITx MicroMasters program credential have the opportunity to apply to the MIT Doctoral Program in Social and Engineering Systems (SES) offered through the MIT Institute for Data, Systems, and Society (IDSS) during the SES admissions cycle (due date: December 15). Credentialed learners will be able to use their credential to demonstrate their preparation in statistics and data science fundamentals to the SES Admissions Committee.

Learners admitted to SES can expect that their MITx MicroMasters program coursework will help prepare them for the SES core classes, and in many cases may or may not be applied toward the SES Information, Systems, and Decision Science course requirements. More information on the MIT SES Doctoral Program can be found here (https://idss.mit.edu/academics/ses_doc/).

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How will having the MITx MicroMasters program credential in Statistics and Data Science change the admissions process for the Statistics, Social and Engineering Systems, and Technology and Public Policy full-time graduate programs?
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The Admissions process for learners who have earned a MicroMasters credential need to participate in the standard admissions process and meet all application requirements for any program to which they apply will not be affected

Successful completion of MicroMasters Program in Statistics and Data Science does not guarantee admissions to MIT SES and TPP graduate programs. Having the MicroMasters program credential provides the admissions committee with significant insight into a learner’s capabilities through the completion of four online courses and one virtually-proctored cumulative exam. We encourage learners to note the completion of MITx MicroMasters program credential in Statistics and Data Science MicroMasters program credential in their application, which the admissions committee will take into consideration. Information on the Doctoral programs at MIT IDSS https://idss.mit.edu/academics/ses_doc/

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What universities accept the MicroMasters program credential for university credit?
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Learners who successfully earn the MITx MicroMasters program credential in Statistics and Data Science are now eligible to earn credit at a number of universities across the globe to fast track their pursuit of a full Master’s degree. Here is a list of these universities and information on the amount of credit offered.

Credit from the MITx MicroMasters program credential in Statistics and Data Science can count towards course requirements for learners admitted to the SES PhD Program.

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How can I contact the faculty member in charge of the MITx MicroMasters program credential in Statistics and Data Science program?
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If your question is about a particular class that you are enrolled in, you can contact the course teams by emailing the address listed on the “About” page for each course. Please direct all other questions about the MITx MicroMasters program credential in Statistics and Data Science to sds-mm@mit.edu

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Is the MITx MicroMasters program credential transferable to other university for credit?
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Yes, it will not only be MIT that will grant credit, there are also a number of universities offering credit for *MITx* MicroMasters programs.

Once you receive the* MITx* MicroMasters program credential, you can apply to these Master’s programs; upon acceptance, your *MITx* MicroMasters program credential will translate into credits toward the Master’s degree, allowing you to accelerate the completion of your graduate studies at one of these universities. To find out which universities are offering credit, please visit here.

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What universities accept the MicroMasters program credential for university credit?
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Learners who successfully earn the MITx MicroMasters program credential in Statistics and Data Science are now eligible to earn credit at a number of universities across the globe to fast track their pursuit of a full Master’s degree. Here is a list of these universities and information on the amount of credit offered.

Credit from the MITx MicroMasters program credential in Statistics and Data Science can count towards course requirements for learners admitted to the SES PhD Program.

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Will MIT add more credit pathway schools in the future?
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Yes, we continue to work with universities globally to grow the pathway credits for MicroMasters program credentials. Please continue to visit our website for updates.

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What if a learner has a desired school for Master’s program but not currently on our pathways list?
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We would love to know and to perhaps build a credit pathway with this school. Please connect with us at micromasters-mit@mit.edu.

### Capstone Exam -- Enrollment Logistics

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What is the Capstone Exam?
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The Capstone Exam is a set of cumulative exams on all content in the four courses in the MicroMasters Program in Statistics and Data Science (SDS). The capstone consists of four 2-hour virtually-proctored exams, roughly corresponding to the 4 courses in the SDS MicroMasters program.

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Who is eligible to take the Capstone Exam?
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**You will be eligible to take this exam only if :**

- You have passed and obtained the certificates for 4 courses (3 core and 1 elective) in the SDS MicroMasters,
- You are verified in the capstone course by the course start date/verify deadline (for the upcoming run, deadline is October 1, 2020), as an ID verified learner with the same edX ID used in all 4 courses.Due to the refund policy, this deadline is not extendable.

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What is a virtually-proctored exam?
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A virtually proctored exam is a timed supervised exam taken online. Learners will follow the instructions in the capstone exam course to download and install the proctoring software on their own computers, and then take the 4 virtually-proctored exams on their own computer.

A proctor ensures the security and integrity of the exam process. A proctor is a liaison between edX and its learners who ensures that testing is done under fair and secure conditions. The proctor’s main responsibilities include verifying a government-issued photo ID, monitoring learners during the exam to ensure they follow the set of exams rules, including not using unauthorized aides, and ensuring learners follow the instructions outlined by the instructor.

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How do I enroll in the Capstone Exam?
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Learners will be allowed to take the set of capstone exams in this course only if you have passed and obtained the certificates for 4 courses (3 core and 1 elective) in the MicroMasters Program in Statistics and Data Science. To enroll in the capstone exam, learners must enroll and verify in the capstone course by the verify deadline, which is the same as the course start date October 1, 2020, using the same edX ID that they have been using for the courses in the SDS MicroMasters Program.

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When does enrollment begin for the Capstone Exam?
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Enrollment for the Capstone Exam begins September 4th, 2020.

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When is it the Capstone Exam deadline?
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The deadline for enrollment is also the verification deadline, **October 1, 2020.** Note the UTC timezone and please find the corresponding time at your location.

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When is the Capstone Exam offered next?
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The Capstone Exam for SDS will be held every other term, i.e. roughly every 8 months.

The current Capstone exam is scheduled **October 28- November 10, 2020.**

You can review the annual course schedule here.

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Will there be a practice exam?
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Yes, there will be an ungraded token practice exam for learners to test that the proctoring software works properly on their systems.

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What is the objective of the Capstone Exam?
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This course consists of four virtually proctored exams, very roughly corresponding to the 4 courses in the SDS MicroMasters program:

- Each exam will be 2 hours in length. Other than the virtual proctoring, each exam will look like the timed exams in the courses with 2 hour time limits. You will practice using the proctoring software in a later section.
- The 4 exams together cover all material in the 4 courses in the SDS MicroMasters program. Please refer to the syllabus of each course for the list of topics covered. The level of difficulty will be comparable to the homework problems in each course.
- The Capstone Exam is an opportunity for you to review extensively and connect the perspectives on the same topics from different courses. Hence, unlike the in course homework and exams, there may be some questions that mix concepts from different courses.
- The capstone exams are much closer to in-class exams, when you will be tested on the knowledge that you have internalized. They are comprehensive, and you will need to think quickly.

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What is the syllabus of the Capstone Exam?
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The 4 exams are divided into two parts, which are open in different periods with different proctoring rules:

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What is the Capstone exams schedule?
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The revised schedule for the current run of the Capstone Exam--

**October 28, 2020 - November 10, 2020.**

**Parts 1 and 2 Open: Wednesday October 28 13:00UTC****Parts 1 and 2 Due: Tuesday November 10 23:59UTC**

**All 4 exams will be open Wednesday, and you will be able to to complete them one at a time in order.**

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Would I need to take the exams in any particular order?
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Yes. Learners must take the Part 1 exams before the Part 2 exams. In Part 1, learners will take the *Probability* exam **before** the *Statistics–Theory* exam, and in Part 2, learners will take the *Statistics* exam **before** the *Machine Learning* exam.

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Can I take the Capstone Exam with the edX mobile app?
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No. No Capstone Exams can be completed using the edX mobile app. Please plan to have a computer that works well with the proctoring software for the duration of the Capstone Exam. See schedule of exams and above.

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What is the Capstone grading policy?
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Each exam counts for 25% of the total grade of the Capstone Exam course. You will need to obtain a total score of at least 50% to pass the Capstone Exam course. (You do NOT need to obtain 60% for each of the 4 exams).

Unlike in the courses, you will receive a letter grade (A, B, C, or F) on top of the raw percentage score.

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What if I have a disability related request for taking the Capstone Exam?
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If you have a disability-related request regarding accessing this exam, please contact us as early in the course as possible (at least 2 weeks in advance of exams opening) to allow us time to respond in advance of deadlines. Requests are reviewed via an interactive process to meet accessibility requirements for learners with disabilities and uphold the academic integrity for MITx.

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What are the computer/system requirements for the Capstone Exam?
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You are responsible to make sure you have a system with internet access that meets the requirements listed at this page. Note that you will have a chance to test the proctoring software before starting the real exams.

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Are we allowed to use cheatsheets for the Capstone Exam?
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Cheatsheets are optional. You are not required to use one.

We intend the cheatsheet as a means for you to review, connect, and summarize ideas, and strongly encourage you to make your own. We expect cheatsheets that you have fully processed and digested to be the only useful ones in 2-hour exams. We also encourage you to make the cheatsheets based on topics rather than courses.

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What are the rules for the cheatsheets for the Capstone Exam?
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You will be allowed to pre-upload and use 2 double-sided cheat sheets for the Part 1 exams, and pre-upload and use 2 more double-sided cheat sheets for Part 2 . Hence, you could choose to prepare up to 4 cheat sheets in total, choose 2 to use in Part 1, and use all of them in Part 2.

Each cheatsheet must be letter-sized (8.5 inches by 11 inches) or A4 and can be double- sided.

- You will be asked to upload cheatsheets
**as pdf**for the first 2 exams before and cheatsheets for the last 2 exams by a specified deadline. - During the exam,s you can access on your screen the cheatsheets that you have uploaded before the corresponding exams open.

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What do I need to bring with me to take the Capstone Exam?
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- Photo Identification which matches the name you use on your edX account (which must be the same as the account you use for the 4 courses).
- (Optional) Basic pens or pencils.
- (Optional) Up to 10 pieces of blank light-colored paper per exam for rough work.

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What will I need for the exam?
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A government-issued photo ID that clearly identifies you by your full name, and that can be used to confirm your identity. Learners will also need to install the proctoring software and ensure that their systems and network satisfy the requirements of the proctoring software.

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How do I prepare an environment to take the Capstone Exam when I am ready to begin the test?
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Learners should set up the following:

- A closed room where no passers-by can communicate with you.
- Your desk must be empty, except for your computer, several pencils/pens, and at most 10 pieces of blank white paper (for rough work).

Enough lighting in the room for the camera to record you properly.You are responsible to make sure you have a system with internet access that meets the requirements listed at this page. Note that you will have a chance to test the proctoring software before starting the real exams.

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What is allowed for Part I Probability Exam, Statistics–Theory Exam?
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During the Probability Exam, and Statistics–Theory Exam you will be allowed to access the following:

- The course websites, including the existing posts in the discussion forum, of all 4 courses in the MicroMasters. These are the course runs which you had enrolled in and passed, and (You will not be allowed to access any current runs of the courses.) The forums of the past courses runs will be closed during the Capstone exams.
**The cheatsheets that you will use have to be uploaded in advance of the Capstone exam.** - PDF-viewers on your own computer, for viewing only:
- Course slides or other pdfs downloaded from the course sites.
- Your uploaded cheatsheets.

- 10 blank pieces of paper for rough work.
- Basic calculator on your computer.
- The following online translators. You are not allowed to open any pre-saved files on any of the translation websites.
- Google translate: https://translate.google.com/
- Fanyi Youdao http://fanyi.youdao.com/
- Bing Translator https://www.bing.com/translator

- File manager, e.g. Finder, Windows Explorer
- Several online calculators and computing software including google calculator and https://www.wolframalpha.com/ We do not expect you to need these tools much in the exam, but allow them for your convenience. You are not allowed to open any pre-saved files on any of the translation websites.

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What is allowed for Part 2: Statistics Exam, Machine Learning Exam?
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In the Statistics Exam, and Machine Learning Exam you will be allowed to access all resources listed above for Part 1, and in addition, **tentatively** the following:

- Certain Python IDEs and code editors on your computer, e.g. Pycharm, Spyder, Jupyter Notebook, etc.
- R IDEs and code editors, e.g. R studio
- Spreadsheet Programs, eg. Excel, Numbers, LibreOffice.

On the internet: Documentation on R and Python.

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What is not allowed during the Capstone Exam?
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The following are not allowed in any of the 4 exams:

- Leaving the room that you are in.
- Covering the camera or being out of camera.
- Stopping the proctoring software.
- Using a cell phone.
- Communicating to anyone or any robots (including sorting algorithms) by any means, e.g. talking to others, email, chatting, Google Glass etc.
- Referring to any physical documents, e.g. dictionaries, notebooks, books etc., except for the 4 blank sheets of paper for rough work.
- Using Multiple Computers or Screens of the same Computer.
- Opening any files other than your cheatsheets and what is downloadable from the exam, and course setsites.
- Accessing any other websites other than what is listed on the previous page.
- Accessing any programs other than what is listed on the previous page.
- Communicating with anyone, through any means, except for technical support by clicking on support button via the proctoring software.
- Retaining any files with exam questions or answers, e.g. no printing or taking screenshots. You must delete, and completely purge with no record, all scripts that you have may have written during the exam.

### More Info

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